This course will cover conceptual and practical aspects of applying bioinformatics approaches to analyze genomic data. In the first part of the course, students will learn approaches to genome sequence assembly, annotation, variant calling, transcriptomics, and regulatory genomics. Students will also be given hands-on experience in these topics through practical work that exposes them to UNIX-like operating systems, cluster computing, and reproducible research. The second part of the course will provide students an opportunity to further develop their genome bioinformatics skills in the context of a short project designed to complement their thesis research. No prior bioinformatics or programming experience is required.

Course Objectives and Expected Learning Outcomes: During the course, students will:
1)	Learn the fundamentals of genome bioinformatics;
2)	Be exposed to some of the approaches used to address questions in genome biology;
3)	Gain skills in working in a UNIX environment on remote computer clusters;
4)	Learn how to do bioinformatics research in a reproducible manner;
5)	Learn how to approach new areas of bioinformatics research;
6)	Develop skills for communicating and documenting bioinformatics research;
7)	Develop intellectual independence.

1)	Introduction to cluster computing
2)	Introduction to the GACRC Cluster
3)	Version control with git and Github
4)	Introduction to Remote Computing with SSH
5)	Introduction to UNIX
6)	Building reproducible workflows in Bioconda
7)	UNIX pipelines & BASH scripting
8)	Introduction to R and Bioconductor
9)	Accessing and manipulating genome sequences
10)	Accessing and manipulating annotation data
11)	Long Read Genome Sequencing/Assembly
12)	Short Read Genome Sequencing/Assembly
13)	Evaluating the Quality of Genome Assemblies
14)	Accessing Public Next Generation Sequencing data
15)	Mapping Next Generation Sequencing data
16)	Variant calling
17)	Genome annotation
18)	Transcriptomics
19)	Regulatory genomics

This topical outline is the general plan for the course; deviations announced to the class by the instructor may be necessary.

Students must be prepared to demonstrate knowledge and be
prepared to discuss all topics, as individuals in the class.
Students are expected to perform their work independently.
However, students are encouraged to collaborate when mastering
approaches and understanding technical details of how 
experiments or bioinformatics approaches work.  Students will 
be expected to abide by the UGA Honor Code in all aspects of 
this course.  Any infringements of the honor code that come to 
the instructor’s attention will be remanded to Academic Affairs 
for disciplinary action.